KR20180126620A - Optimize warehouse layouts based on customizable goals - Google Patents

Abstract

Exemplary methods and systems enable warehouse relocation to an optimal layout determined according to customizable goals. Exemplary methods include receiving information from warehouse and warehouse items in a warehouse management system (WMS), delivering new items expected to arrive at the warehouse on future dates, and future dates Identifying an expected shipment of goods, including items present in the warehouse marked for shipment, determining an optimal layout of items in the warehouse of the current date based on shipment shipment estimates, Determining an amount of time to relocate the articles by one or more of the robotic devices that relocate the articles to an optimal layout based on the value of the article, To be relocated.

Description

Optimize warehouse layouts based on customizable goals

Warehouses can be used to store goods by a variety of different types of businesses, including manufacturers, wholesalers, and transportation companies. Exemplary archival articles may include raw materials, parts or components, packaging materials, and finished articles. In some cases, warehouses are equipped with loading docks that allow goods to be loaded and unloaded onto delivery trucks or other types of vehicles. The warehouse can also use a row of pallet racks to allow storage of flat transport structures containing pallets, i.e., box stacks or other objects. In addition, the warehouse may have a machine or a vehicle for lifting and moving goods or commodity pallets, such as cranes and forklifts. To operate machines, vehicles, and other equipment, human operators may be employed. In some cases, one or more of the machines or vehicles may be a robotic device that is guided by a computer control system.

In one example, in a warehouse management system (WMS), receiving real-time location data of goods in a warehouse and real-time location data of goods in a warehouse, Identifying an expected shipment of goods, including an item present in the warehouse marked for delivery on the date of the shipment. The identifying step is performed by the WMS and is based on one or more of the receipt record, order fulfillment, and shipment history. The method also includes the steps of determining an optimal layout of the articles based on the expected shipment of articles, and determining the amount of time for the robot device to relocate the articles to the optimal layout based on the time measurements for performing the tasks . The method also includes determining to relocate the items of the warehouse based on the amount of time to relocate the articles less than the threshold time amount, and causing the robotic device to relocate the articles to an optimal layout.

In another example, a system is described that includes a data storage that includes instructions executable by a processor to cause a robotic device, processor, and system within a warehouse to perform operations. These operations include: receiving real-time inventory of goods in the warehouse and real-time location data of the goods; and receiving new items expected to arrive at the warehouse on future dates and articles present in the warehouse marked for delivery on future dates Lt; RTI ID = 0.0 > a < / RTI > The identifying operation is based on at least one of a receipt record, an order fulfillment record, and a shipping record. These operations may also include determining an optimal layout of the articles based on the expected shipment of the article; Determining an amount of time for the robot device to relocate the articles to an optimal layout based on a time measurement for performing the task; Determining to relocate the items of the warehouse based on the amount of time to relocate the items less than the threshold time amount; And causing the robot device to relocate the articles in an optimal layout.

In yet another example, a non-transient computer-readable medium having stored thereon program instructions for causing a computing system to perform operations when executed by a computing system including at least one processor is described. These operations include: receiving real-time inventory of goods in the warehouse and real-time location data of the goods; and receiving new items expected to arrive at the warehouse on future dates and articles present in the warehouse marked for delivery on future dates Lt; RTI ID = 0.0 > a < / RTI > The identifying operation is based on one or more of the receipt record, order fulfillment, and shipment history. These operations may also include determining an optimal layout of the articles based on the expected shipment of the article; Determining an amount of time for the robot device to relocate the articles to an optimal layout based on a time measurement for performing the task; Determining to relocate the items of the warehouse based on the amount of time to relocate the items less than the threshold time amount; And causing the robot device to relocate the articles in an optimal layout.

In yet another aspect, a system is provided that includes means for receiving, in a warehouse management system (WMS), real-time inventory of goods in a warehouse and real-time location data of goods. The system also includes means for identifying new shipments expected to be placed in the warehouse on future dates and shipments expected to ship, including those present in the warehouse marked for delivery on future dates. The system also includes means for determining an optimal layout of the articles based on the expected shipment of the articles. The system also includes means for the robot device to determine the amount of time for the robot device to relocate the articles to the optimal layout based on the time measurements for performing the tasks. The system also includes means for determining to relocate the items of the warehouse based on the amount of time for relocating the articles to less than the threshold time amount, and means for causing the robot device to relocate the articles to an optimal layout.

The foregoing summary is illustrative only and is not intended to be limiting in any way. In addition to the exemplary aspects, implementations, and features described above, additional aspects, implementations, and features will become apparent with reference to the drawings and the following detailed description.

Figure 1 illustrates an exemplary repository in accordance with at least some implementations described herein.
2 is a simplified block diagram illustrating components of an exemplary computing system in accordance with at least some implementations described herein.
FIG. 3 is a flow chart of an exemplary methodology in accordance with at least some implementations described herein.
Figure 4 shows an exemplary layout of a warehouse, including a plurality of article palettes and a docking station, labeled as pallets A through H;
Figure 5 shows an exemplary relocation of palettes A through H to an optimal layout.
6 illustrates an exemplary relocation of the pallets A, E, and F for an exemplary layout.
Fig. 7 shows another exemplary layout of a warehouse, including a number of article palettes labeled as Palettes A through H, and new palettes I through K received at the dockyard.
Figure 8 shows an exemplary optimal layout of a warehouse based on the maximum storage capacity placement of the warehouse.

Exemplary methods and systems are described herein. It is to be understood that the terms "exemplary "," exemplary ", and "exemplary" are used herein to mean "serving as an example, instance, or illustration. Any embodiment or feature described herein as "exemplary " or" exemplary " or "exemplary " is not necessarily to be construed as preferred or advantageous over other implementations or features. The exemplary implementations described herein are not meant to be limiting. Aspects of the present disclosure, as broadly described herein and illustrated in the drawings, may be arranged, substituted, combined, separated, and designed in a variety of different configurations, all of which are expressly contemplated herein It will be easy to understand that it becomes an object. In addition, in this disclosure, unless otherwise indicated and / or the context clearly dictates otherwise, the term "a" or "an" means at least one and the term " do.

As used herein, the term "warehouse" may refer to any physical environment in which articles, or article palettes, can be manipulated, processed and / or stored by a robotic device. In some instances, the warehouse may be a single physical building or structure. In another example, some fixed components may be installed in the environment or otherwise disposed before or during processing of the object. In a further example, the warehouse may also include a plurality of distinct physical structures or physical spaces that are not covered by physical structures and / or buildings.

An exemplary warehouse may include a control system configured to manage groups of same or different robotic devices and robotic devices. In the context of a warehouse, such a control system may be referred to as a warehouse management system (WMS). The warehouse may also include various articles (e.g., articles) disposed on the pallets, and the pallets may be placed at various locations within the warehouse. For example, the pallets may be placed directly on the bottom of the warehouse or stacked on another pallet, placed in a pallet rack, and / or stored in a shipping container. Also, the warehouse may be disposed separately (not on a pallet), and may include customized containers, items contained in a box, or items not included in any container.

A robotic device group can be used for warehouse configuration for a number of different applications. One possible application involves order fulfillment (e.g., for an individual customer), in which case the pallet can be opened and individual items from the pallet can be packaged in a box to fulfill an individual order. Another possible application involves distributing (e.g., to a store or other warehouse) and mixing pallets containing a group of different types of items (i.e., different types of products) for shipping to a store Lt; / RTI > A further possible application includes cross-docking, which may include transporting between shipping containers without storing anything (e.g., the items may be transported by four 40-foot trailers And loaded into three lightweight tractor trailers, and can also be palletized). Numerous other applications are also possible.

In general, the manner in which the pallets are placed in the warehouse can depend on a variety of factors. These factors include, among others, activity history in a warehouse, history of pallet positions, demand history for a given article, trends of articles placed in a warehouse, trends of articles shipped from a warehouse, received orders for articles, (For example, promotional offers such as day-to-day deliveries), and pallets to be placed in the warehouse, anticipated activities, anticipated demand for a given item, anticipated items to be placed in the warehouse, anticipated items to be shipped from the warehouse, And / or robot availability. The WMS can be configured to use these and other factors in machine learning to facilitate improved management of the warehouse, including placement and relocation of pallets within the warehouse.

An exemplary method and system for autonomously relocating, i.e. "shuffling" palettes within a warehouse is described herein. According to an exemplary method, the WMS provides real-time article information, including real-time locations of article palettes in a warehouse, real-time inventory of articles in a warehouse, and real-time content of each palette (e.g. Received, determined, or otherwise accessed. The WMS may also include a history of pallet relocation history (e.g., information regarding where, why, and / or when the pallet is moved from one place to another), estimates of items to be placed in the warehouse, Or otherwise access other warehouse information, such as, for example, the likelihood,

The WMS also includes new items that are expected to arrive in the warehouse on future dates, as well as access to order fulfillment and shipment records, as well as receipt records, and items that are present in the warehouse marked for delivery on future dates. After identifying an expected shipment of goods, an optimal layout of the items in the warehouse of the current date can be determined based on the shipment estimate of the shipment.

In addition, the WMS can determine what resources are needed to relocate the warehouse to the optimal layout, such as the time it takes for the robot device to relocate the pallets. If the WMS determines that the resource meets certain criteria, the WMS may instruct the robot device to relocate the palettes. If not, the WMS may not instruct the robot device to relocate the palettes until the WMS determines that the resource meets certain criteria.

In the examples, in order to actually facilitate this, the WMS can receive, determine, or otherwise access real-time robot information related to robot activity in the warehouse. As an example, the real-time robot information may include, in particular, real-time position updates of the robot device, real-time task progress updates for ongoing and / or completed robot tasks, task schedules, and the time it takes for the robot device to perform various tasks And may include measurement values. The WMS can then use at least real-time robot information to determine the time it takes for the robot device to relocate the pallets to the optimal dense grid layout. If the amount of time is less than the threshold amount of time, the WMS may instruct the robot device to relocate the pallets to an optimal dense grid layout. The threshold can be, for example, dynamic and can be based on expected or actual robot availability. In addition, the WMS may consider parameters other than time, such as power usage, carbon emissions, article movement distance, etc., when deciding whether to direct the robot device to relocate the pallets.

Dynamically and autonomously relocating pallets in a warehouse can provide a variety of industrial and business benefits. For example, the use of WMS and robotic devices can greatly reduce or eliminate the need for manpower when relocating warehouses. As another example, because the demand for an item changes over time, the WMS changes the layout of the pallets to best reflect the current demand at various points in time, or best reflects the expected demand at a future point in time The layout of the palettes can be aggressively changed. As yet another example, when the available space in a warehouse increases or decreases, the WMS balances other considerations such as consideration of available space, demand, ease of access to the item, and so on, It can be determined whether or not the available space in the warehouse can be best utilized. Other examples are also possible.

In an alternative implementation, one or more computing entities associated with a warehouse, such as a WMS and / or other computing system, may collect, update, and process article information and / or robotic information less frequently than real time for reception by a WMS And / or < / RTI >

Reference will now be made in detail to various implementations of which examples are illustrated in the accompanying drawings. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure and the described implementations. However, the present disclosure may be practiced without some of these specific details. In other instances, well-known methods, procedures, components, and circuits have not been described in detail so as not to unnecessarily obscure aspects of the implementations.

Referring now to the drawings, FIG. 1 illustrates an exemplary warehouse 100 in accordance with at least some implementations described herein. The warehouse 100 includes various types of robotic devices that can be controlled to cooperate to perform tasks related to the processing of articles, pallets, and the like within a warehouse. While certain exemplary types and numbers of different robotic devices are shown herein for purposes of illustration, the warehouse may employ more or fewer robotic devices and may omit certain types shown herein , Other types of robotic devices not explicitly shown.

One exemplary type of robotic device shown in Fig. 1 is an autonomous fork truck 102, which transports a box pallet and / or a box pallet (e.g., to place a pallet on a rack for storage) Or a forklift that can be used to transport and / or lift the box itself. Another exemplary type of robotic device shown is an autonomous guide-type vehicle (e.g., an automotive vehicle) that can be a relatively small mobile device having wheels that can serve to transport individual articles or other objects from one location to another within a warehouse an autonomous guided vehicle (AGV) 104. Additional illustrative types of robotic devices include robotic truck loader / unloader 106, optical sensors for facilitating loading and / or unloading of goods and / or pallets, as well as robotic manipulators, to trucks or other vehicles ≪ / RTI > For example, the robotic truck derailer 106 may be used to load a pallet or individual item on a delivery truck 108 located in a shipping dock 110 of the warehouse. In some instances, movement of the delivery truck 108 (e.g., delivering the package to another warehouse) may also be coordinated with the robotic device in the warehouse.

Other types of mobile devices other than those shown herein may also be included or alternatively. In some instances, one or more robotic devices may utilize a different transport mode in addition to wheels on the ground. For example, the one or more robotic devices can be airborne (e. G., Quad-copter) and can be used for tasks such as moving objects or collecting environmental sensor data. Any of the robotic devices described herein may be used in various applications including, but not limited to, force sensors, proximity sensors, load sensors, position sensors, touch sensors, depth sensors, ultrasonic distance sensors, infrared sensors, Global Positioning System (GPS) a sensor, a radio sensor, a radio sensor, a wireless sensor, a compass, a smoke sensor, an optical sensor, an audio sensor, a microphone, a speaker, a radar, a camera (for example, (E.g., color cameras, grayscale cameras, and / or infrared cameras), depth sensors (e.g., red green blue plus depth (RGB-D), lasers, light detection and ranging And / or a range sensor (e. G., An ultrasonic transducer) and / or a range sensor (e. G., A gyroscope, an accelerometer, an inertial measurement device And / or infrared) may include one or more sensor (s) and the like. The sensor (s) may provide sensor data to the processor (s) to allow for proper interaction of the robot device with the environment. Additionally, the robotic device may also include one or more power source (s) configured to power various components of the robotic device. Any type of power source, such as, for example, a gasoline engine or battery, may be used.

In a further example, the warehouse 100 may also include various fixed components or fixed robotic devices. A fixed robotic device may be used to move or otherwise manipulate the article. For example, the pedestal robot 112 may include a raised robot arm on a pillar fixed to a first floor within a warehouse. The holding robot 112 can be controlled to dispense articles among other robots and / or stack and unpack the article pallets. For example, the holding robot 112 can pick up and move boxes from a nearby pallet and distribute the items to individual AGVs 104 for transport to other locations in the warehouse.

In a further example, the warehouse 100 may include additional fixed components, such as a storage rack (not shown), which may be used to store pallets and / or other objects within the warehouse. Such a storage rack may be designed and arranged to facilitate interaction with one or more robotic devices, such as an autonomous fork truck 102. [ In addition to, or as an alternative to, the storage rack, a predetermined ground space within the warehouse 100 may be selected and used to store the pallet. For example, some pallets may be placed in a warehouse environment at selected locations for a predetermined period of time to allow the pallets to be picked up, distributed or processed by the robotic device. Any fixed component in the warehouse 100 may have one or more sensors, as described herein.

In some instances, any or all of the robotic devices in the warehouse 100 may include one or more sensors, one or more computers, and one or more robotic arms or robotic manipulators. The sensor may be used to perform various operations, such as scanning an area within the warehouse 100 to capture visual data and / or three-dimensional (3D) depth information. The data from the scan may then be incorporated into the representation of the larger area to provide digital environment reconstruction. In a further example, the reconstructed environment can be used to identify an article, a palette, or other object to be picked up, to determine the pickup position of the article or pallet, and / or to plan the collision- have. The warehouse 100 may also include a sensor, such as a camera or other type of sensor, that is not connected to the robotic device. For example, various sensors may be attached to various locations in the warehouse, such as walls, ceilings, and the like.

As shown in FIG. 1, the warehouse 100 includes a variety of palettes, each of which may include one type of article or may include a plurality of types of articles. As an example, the warehouse 100 includes rows 114, 116, 118, 120, 122 and 124, each of which includes one line of pallets containing the same type of article. For example, each of the pallets of row 114, row 118, and row 124 may comprise a first type of article, and each of the pallets of row 116 and row 122 may comprise a first Two types of articles, and each of the pallets of row 120 may include a third type of article.

Some palettes within the rows 114, 116, 118, 120, 122, and 124 may be viewed as a "full" palette, ie, a palette containing the maximum number of articles assigned per pallet. The maximum number of items assigned to each palette may be the same or different for a plurality of palettes, and may be a quantity defined by the WMS or by a human. In addition, the maximum quantity of articles to be allocated per pallet may depend on various factors such as the pallet structure (e.g., the maximum weight that the pallet can support). By way of comparison, the warehouse 100 may also include a variety of non-filled pallets, such as pallets 126, pallets 128, pallets 130, and pallets 132. Each of these palettes may contain the same type of article or may comprise a different type of article.

The manner in which the pallets are disposed in the warehouse 100 shown in Fig. 1 may be an example of a deep lane layout. For example, row 114 and row 116 may together form a first lane and row 118 and row 120 may together form a second lane and row 122 and row 116 may form a second lane, (124) may together form a third lane. Each of the first lane, the second lane, and the third lane is coupled to a second lane, such as a distance that allows a robot device (e.g., autonomic fork truck 102) to move between lanes and access the palette within the lanes, Can be separated by a predetermined distance.

Lanes, rows, and palettes may be configured differently from the example shown in FIG. For example, in another deep lane layout, the entire first lane may only include a first type of article, and the entire second lane may only comprise a second different type of article. Also, the number of pallets constituting the width and length of each lane can be increased or decreased.

In some instances, the warehouse 100 may further include a battery exchange / charging station (not shown). In some instances, some or all of the mobile robot devices, such as autonomic fork truck 102 or AGV 104, may periodically receive charged batteries from a battery exchange station having a plurality of battery chargers. In one example, the battery exchange station can replace the old battery of the robotic device with a charged battery, thereby preventing the robotic device from sitting down and waiting for the battery to be charged. The battery exchange station may include a robot manipulator such as a robot arm. The robot manipulator may remove the battery from the respective mobile robot device and attach the battery to an available battery charger. The robot manipulator can then move the charged battery located at the battery exchange station into the mobile robot device to replace the removed battery. For example, an AGV with a weak battery can be controlled to move to a battery exchange station where the robot arm pulls the battery out of the AGV, puts it into the charger, and provides a fresh battery to the AGV.

In the examples, before determining the placement of other objects, such as any pallets, as well as any fixed robotic device or components discussed above, one or more robotic devices are moved to the warehouse 100 to map a map of the warehouse 100 space Can be generated. As used herein, a "map" refers to information that indicates the location of elements within an area of an environment and / or represents relationships to other elements or environments of a given element. In an exemplary implementation, a map is a digital map that is determined by collecting and compiling data representing relationships between elements within a given environment, and then formatting the data into a virtual format such as a virtual 2D or 3D image. The map may be a real-time or non-real-time representation of the elements of interest and the environment, and describes in detail such points of interest, elements, and / or on these elements and / or in the environment.

Once map information is available, a computing system, such as a WMS, can determine how to lay out these components in an available space (e.g., by executing a simulation). In some cases, the layout may be selected to minimize the amount of space occupied by the object. The palettes can be placed at predetermined positions or in other examples at random. Also, the palettes can be deployed using an intelligent optimization approach based on a number of factors described herein, where the predetermined location or randomness can also be one or more factors.

To coordinate the operation of various devices within the warehouse 100 (e.g., robotics devices, and possibly other components such as battery charging stations, remote-controlled loading door doors, remote-controlled lamps, etc.), a remote cloud- A global control system, such as a server system, may communicate with some or all of the components (e.g., via wireless communication) and / or with a separate local control system of the individual components. Any computing system described herein, such as WMS, may take the form of such a global control system.

2 is a simplified block diagram illustrating components of an exemplary computing system 200 in accordance with at least some implementations described herein. For example, the computing system 200 may serve as a WMS and may include a plurality of storage devices, such as a warehouse 100, such as the warehouse 100, which may include dynamically controlling the operation of a robotic device or other component within the warehouse, And can control aspects. Accordingly, computing system 200 may include various components such as processor (s) 202, data storage unit 204, communication interface 206, and / or user interface 208. The components of the computing system 200 may be connected to each other (or another device, system, or other entity) via a connection mechanism 210. In this disclosure, the term "connection mechanism" means a mechanism that facilitates communication between two or more devices, systems, or other entities. For example, the connection mechanism may be a simple mechanism such as a cable or system bus, or a relatively complex mechanism such as a packet-based communication network (e.g., the Internet). In some cases, the connection mechanism may include a non-tangible medium (e.g., if the connection is wireless). The computing system 200 may include more or fewer components in other exemplary implementations.

The processor 202 may take the form of a general purpose processor (e.g., a microprocessor) and / or a special purpose processor (e.g., a digital signal processor (DSP)). In some instances, computing system 200 may include a combination of processors.

Data storage unit 204 may include one or more volatile, non-volatile, removable and / or non-removable storage components such as magnetic, optical or flash storage, and / or may be integrated in whole or in part with processor 202 have. Accordingly, the data storage unit 204 may include one or more program instructions (e. G., Program instructions) that, when executed by the processor 202, cause the computing system 200 to perform one or more operations and / or functions, such as those described in this disclosure Readable storage medium in which program logic and / or machine code, such as compiled or non-compiled program logic and / or machine code, is stored. The computing system 200 may be configured to perform one or more operations and / or functions, such as those described in this disclosure. These program instructions may define an individual software application and / or a portion thereof. In some instances, computing system 200 may execute program instructions in response to receiving input from, for example, from communication interface 206 and / or user interface 208. The data storage unit 204 may also store other types of data, such as the types described in this disclosure.

The communication interface 206 may allow the computing system 200 to access and / or communicate with another entity in accordance with one or more protocols. In one example, the communication interface 206 may be a wired interface, such as an Ethernet interface or a high-definition serial-digital-interface (HD-SDI). In another example, the communication interface 206 may be a wireless interface, such as a cellular or Wi-Fi interface. The connection may be a direct connection or an indirect connection and the latter is a connection that traverses or traverses one or more entities, such as a router, switcher, or other network device. Likewise, the transmission may be direct transmission or indirect transmission.

The user interface 208 may facilitate interaction between the computing system 200 and a user of the computing system 200, if applicable. Thus, the user interface 208 may be implemented as an input component, such as a keyboard, a keypad, a mouse, a touch-sensitive panel, a microphone and / or a camera, and / or a display device (which may be combined with a touch- , A sound speaker, and / or an output component, such as a haptic feedback system. More generally, the user interface 208 may include hardware and / or software components that facilitate interaction between the computing system 200 and a user of the computing device system.

As indicated above, the computing system 200 may be configured to dynamically control aspects of the warehouse, such as by coordinating the operation of a robotic device operating in a warehouse. As an example, the computing system 200 may determine a schedule for a given robot device to represent a series of tasks to be performed by the robot device for a whole period of time, and may include subsequent information received from the robot device (e.g., sensor data, Progress updates), other robotic devices, and / or other systems located in the warehouse (e.g., sensor systems). As another example, if the computing system predicts that more than one robotic device may be needed to assist another task in the same area for a predetermined period of time, the computing system 200 may determine that two or more robotic devices Including aligning the schedules so that they are located in the same area. ≪ RTI ID = 0.0 > [0035] < / RTI > As another example, the computing system 200 can avoid the occurrence of excess traffic in the warehouse by preparing a schedule so that it does not have a high amount of robotic devices of a critical amount performing work in the same area for the same period of time. As yet another example, the computing system 200 may cancel the pickup of the scheduled pallet of the first robotic device when the second robotic device is closer to the palette than the first robotic device, The schedule of one or more robotic devices can be changed to save resources by instructing the robot device to pick up the pallet.

In some instances, the computing system 200 may function as or include a central planning system that assigns tasks to different robot devices. Herein, "job" refers to an operation assigned to the at least one entity to be performed by at least one entity. In an exemplary implementation, this task is assigned to at least one entity by a system that monitors, controls, or otherwise manages at least one entity to facilitate performing the task by the at least one entity.

The central planning system may employ various scheduling algorithms to determine which device will complete a task at what time. For example, the central planning system may assign tasks to robots to minimize the overall cost of the particular robots performing the tasks. In a further example, the central planning system can optimize over one or more different resources such as time, space, or energy utilization. In a further example, the planning or scheduling system may also incorporate the geometry and physical aspects of boxing, packing, or storage.

The plan control may also be distributed across the individual system components. For example, the computing system 200 may issue commands in accordance with a global system plan, and the individual system components may operate in accordance with a separate local plan. In addition, details of the different levels can be included in the global plan, along with other aspects that individual robot devices can plan locally. For example, although mobile robot devices may be assigned to a target destination by a global planner, the entire path to reach these target destinations may be locally planned or changed.

To facilitate planning control, the computing system 200 may employ a variety of techniques to monitor the location of the robotic device in the warehouse 100. [ These locations may be real-time locations. To facilitate planning control, in some implementations, the robotic devices may be configured to "publish" (e.g., transmit) their position continuously or periodically to the computing system 200 such that the computing system 200 Thereby updating the position of the robot devices. The computing system 200 and / or the robotic device may also employ other techniques to facilitate monitoring the location of the robotic device.

The term " real time " refers to an actual time at which a process or an event occurs, whereby a real time position is determined within a critical time amount (e.g., determined within a few seconds) Lt; RTI ID = 0.0 > a < / RTI >

In a further example, the central planning system may be utilized in conjunction with a local vision system on an individual robotic device to coordinate the functionality of the various robotic devices. For example, the central planning system can be used to move robot devices at least relatively close to where they need to go. However, unless the robot device is bolted to the rails or other measured components are used to precisely control the robot position, it may be difficult for the central planning system to command the robot with millimeter accuracy. Thus, a local vision system and scheme for each robotic device can be used to allow flexibility among different robotic devices. A general planner may be used to move the robot device closer to the target location that the local vision system of the robot device will assume. In some instances, most robotic functions can be position-controlled to move the robot relatively close to the target location, and vision systems and handshakes can be used as needed for local control.

The visual handshake can allow two robotic devices to identify each other and perform cooperative operations within the warehouse 100 using quick response (QR ) codes or other characteristics. In a further example, the article (e.g., the package to be shipped) may also be provided with a visual tag, either instead or in place. The visual tag may be used by the robotic device to perform operations on the article using a local vision system. In one example, the tag may be used to facilitate manipulation of the article by the robotic device. For example, a tag at one location on the pallet can be used to notify the forklift of the location and method of lifting the pallet.

In additional examples, the robotic devices may utilize their local vision system to scan and identify individual articles or article palettes of articles during operations in which the robotic device needs to manipulate the articles / pallets in a predetermined manner. To facilitate this in part, for example, a given article / palette may include machine-readable code (e.g., a QR code or bar code) having encoded information about a given article / palette. As a result of the scan, the machine-readable code may provide information to the local computing system of the robot device and / or to a given article / palette to the computing system 200. For example, in the case of a palette, this information may include the type of article contained in the palette. The pallets may also include one or more boxes known to be located as part of a radio frequency identification (RFID) tag and / or palette contained on the pallet. In addition, the acquisition of this information by scanning the pallet or communicating with the RFID can be accomplished in a variety of different types of information: (i) where the pallet was in the warehouse, (ii) how many pallets were moved, (iii) (Iv) an indication of damage to the pallet, if any; and (v) whether the pallet is marked for delivery to another area of the warehouse (eg, for storage in a dock, or another area) The history of the pallet. A given article / palette may additionally or alternatively include a label or other source of such information that the robotic device can scan to identify the article / palette and obtain such information.

Scanning the article / pallet in this manner may have a variety of advantages, such as locating and tracking the article / pallet as the article / pallet is moved into and out of the warehouse 100. In addition, the potential benefit of this scan is that transparency is added both on the supplier side and on the consumer side. On the supplier side, for example, information about the current location of the inventory can be used to avoid excessive inventory or to move the goods / pallets to a different location or warehouse where demand is anticipated. On the consumer side, for example, information about the current location of the article can be used to determine when the article / pallet will be delivered with improved accuracy

Within additional examples, the computing system 200 may optimize the placement and / or strategy for fixed and / or mobile components over time. For example, the computing system 200 (e.g., a cloud-based server system) may integrate data and information from and / or from external robotic devices within the warehouse. The strategy can then be improved over time to allow the robot device to use less space, less time, less power, less electricity, or to optimize over other variables. In some instances, the optimization may be up to multiple warehouses, perhaps including other warehouses with other robotic devices and / or traditional warehouses without such robotic devices. For example, the computing system 200 may integrate information about delivery vehicles and transit times between facilities into a central plan.

Similarly, computing system 200 may be configured to meet existing demand for products (e.g., current order for product), meet expected demand for the product, Etc., can be optimized over time.

In some instances, the central planning system may fail occasionally, such as when the robotic device is unable to move or when the article is lost in some place and lost. The local vision system may also provide robustness by inserting redundancy to handle the case where the central planner fails. For example, because an automated pallet jack delivers and identifies the item, the pallet jack can transfer information to remote cloud-based server systems. This information can be used to correct errors in the central planning, to help locate the robot device, or to identify lost items.

In a further example, the computing system 200 may dynamically update the map of the warehouse 100 and the object being processed by the robotic device. In some instances, the map may be continuously updated with information about the dynamic object (e.g., the moving robot device and the article / pallet moved by the robotic device). In a further example, the dynamic map may include information about all current placement of objects within a warehouse (or across multiple warehouses), as well as information about the current location of objects within a warehouse (e.g., a few seconds, (E.g., an incoming order, several months, or several years), and the like. For example, the map may show the current location of moving robot devices and the future expected location of the robot devices, which may be used to coordinate activity among the robot devices. The map may also show the current location of the item being processed, as well as the expected location of the item in the future (e.g., where the item is currently located and when the item is expected to be shipped). The map can also show the expected location of the item that has not yet arrived at the warehouse. For example, the computing system 200 may be configured to provide a map display of the order history for the items, the expected order, the history of the pallet relocation, and / or the location where the article pallets should be placed in the warehouse upon arrival at the warehouse Lt; RTI ID = 0.0 > and / or < / RTI >

Consistent with the foregoing discussion, the computing system 200 may also schedule battery replacement, power charging, and any other scheduled maintenance that may be required. For example, an individual mobile robot device may be configured to monitor battery charge status. The robotic devices may send information to the computing system 200 indicating the status of their batteries. This information can be used by the computing system 200 to schedule battery replacement for an individual robot device when needed or convenient.

As discussed above, the computing system 200 may serve as a WMS that executes instructions stored in the data storage unit 204 to determine the optimal layout of the warehouse. Traditionally, the arrangement of the warehouse is static and the pallet is placed at a preset location. However, as shipments vary (e. G., Daily, seasonally), the methods described herein may enable dynamic relocation of warehouses based on a number of possible factors. For example, a seasonal item may be placed behind the warehouse when these items are out of season, and an excess inventory of similar items may also be placed rearward. The layout can be dynamically determined without being constrained to any fixed layout of the warehouse, and any layout can be optimized based on factors considered. Through the contents of known palettes as well as the physical location of all the pallets in the warehouse, the shipping order can be accessed to determine the goods to be processed for shipment and the goods receipt to be accessed to determine what goods are expected to be received. All of these factors can be processed to create an optimal layout of the warehouse at the current time.

The optimal layout may be based on customizable goals, such as improving the storage capacity of the warehouse. If a storage capacity is required, the layout can be modified to compromise the take-out throughput (e.g., access to the pallet's articles) to increase the storage capacity using a narrower passage instead of a wider width. The layout can be optimized for one day or one year of the season, or to optimize storage capacity or throughput throughput.

FIG. 3 is a flow chart of an exemplary method 300 in accordance with at least some implementations described herein. The method 300 shown in FIG. 3 may be used, for example, with the devices, components, and systems shown in FIGS. 1 and 2, or performed by a combination of any of the components of these drawings And presents an implementation of a method that can be implemented. The method 300 may include one or more actions, or actions, represented by one or more of the blocks 302-312. Although blocks are shown in a sequential order, these blocks may be performed in some instances in parallel, and / or may be performed in a different order than those described herein. In addition, the various blocks may be combined into fewer blocks, divided into additional blocks, and / or removed based on the desired implementation.

In addition, for method 300 and other processes and methods disclosed herein, the flowchart illustrates the operation of one possible implementation. In this regard, each block may represent a module, segment, or portion of program code that includes one or more instructions executable by one or more processors to implement a particular logical operation or step in the process. The program code may be stored on any type of computer readable medium, such as, for example, a storage device including a disk or a hard drive. Computer-readable media can include non-volatile computer-readable media, such as a register-memory, a processor-cache, and a computer-readable medium that stores data for a short period of time, such as random access memory (RAM). Computer-readable media also includes non-volatile media such as, for example, read-only memory (ROM), optical or magnetic disks, secondary or permanent long-term storage such as compact disc read only memory . The computer readable medium may also be any other volatile or nonvolatile storage system. The computer-readable medium may be, for example, a computer readable storage medium, a type of storage device, or any other article of manufacture.

Further, for the method 300 and other processes and methods disclosed herein, each block in FIG. 3 may represent a circuit that is wired to perform certain logical operations in the process.

The operations of the methods disclosed herein, and other methods and operations of the process, are described in some instances as being performed by a WMS, such as computing system 200, or the like. However, these operations may be performed in whole or in part by other entities or combinations of entities. For example, these operations may be managed by a smaller peer-to-peer network capable of managing portions of the robotic device, or by a central server capable of distributing operations to the server. In addition, in the examples, the WMS may be a cloud-based computing system or another entity configured to manage at least some of the robotic devices to relocate the layout of the warehouse.

At block 302, the method 300 includes receiving, at a warehouse management system (WMS), information of warehouses and warehouses, including real-time inventory of goods in the warehouse and real-time location data associated with items placed in the warehouse . The items in the warehouse are placed on a pallet, and the WMS receives information about the contents of each pallet as well as the location of the pallets in the warehouse. In some examples, information about the location of the pallet, and other real-time location data, may be provided to a sensor, tracker, transmitter, or pallet or object in a warehouse and its environment (e.g., loading bay, parking area, adjacent storage unit, Lt; RTI ID = 0.0 > WMS < / RTI > WMS can plan and manage warehouse layout and activities. For example, the WMS can use real-time inventory to determine where to store items to be stocked on the next business day based on purchase order and customer order data, and to determine where to store the items once they have been received.

At block 304, the method 300 determines, based on access by the WMS to one or more of the goods receipt record, the order fulfillment, and the shipment history, one or more new items expected to be put into the warehouse on a future date, And identifying an expected shipment of the item including one or more items present in the warehouse marked for delivery on a date. Order fulfillment and shipment records can be electronically transferred to WMS or stored in WMS. In addition, WMS can access order fulfillment and shipment records over the network.

At block 306, the method 300 includes determining an optimal layout of items in the warehouse of the current date based on the shipment estimate. The optimal layout of the items in the warehouse may also be determined based on business goals, such as a promotion date for the item or a quantity estimate of the item to be delivered.

Exemplary layouts of the warehouse are shown in Figs. 4-8 as described in detail below.

The determination of the optimal layout of the items in the warehouse of the current date can be based on many factors. Optimization can be determined by analyzing previously performed relocation to determine the cost of switching the layout. The optimization may be based on the output of the cost function taking into account multiple parameters. Some parameters include the amount of time that inventory is expected to be exhausted, the amount of storage capacity required for the incoming item, and one or more deadlines for shipping the item.

Further, the determination of the optimal layout can be performed by accessing the configuration of the stored warehouse or from the past placement of the warehouse. For example, items in a warehouse can be configured in a desired manner, and specific configurations can be recorded and stored in memory, such as by photographing a warehouse to record physical locations and locations of pallets. This configuration can be associated with specific parameters, such as storage capacity parameters, export throughput parameters, etc., and the user can enter parameters into the WMS for future relocation of the warehouse, And determine an associated optimal layout based on parameter inputs.

One exemplary layout may include a dense grid layout in which the pallets are kept compact so that when the pallets need to be moved for various purposes, ) Palettes still allow the robotic device to access more easily, thereby controlling how the robotic device accesses the pallet. The dense grid layout can have various properties. At a minimum, for example, the distance of a given pallet from the center of the driving lane of the dense grid layout may be related to the demand for that pallet.

As another example, an optimal layout may include a deep lane layout that may be defined by various characteristics. At a minimum, for example, a deep lane layout may include groups of palettes arranged in each lane, which can not be immediately accessed from a moving or driving lane for reasons that some palettes lie behind other palettes. Other layouts are also possible.

At block 308, the method 300 includes the steps of one or more robotic devices that relocate items in the warehouse by relocating the articles to an optimal layout, based on time measurements for the robotic devices in one or more robotic devices to perform tasks And determining the amount of time. A plurality of robotic devices may also be used for this purpose. Compared to human labor, which can introduce variability within an event, robotic devices can perform tasks within a known time frame. Thus, the time measurement may be a fixed time measurement. It can be determined that moving a pallet to a new location across a warehouse by a particular robot device will require a certain amount of time. In addition, in the robotic device suite, the WMS can program each individual robotic device in a manner such that none of the robotic devices cross paths or cause conflicts with any others. This allows each robot device to operate independently or collectively efficiently, and allows the flight to operate efficiently to perform repository relocation.

The WMS can access a database that stores a known amount of time for performing a specific task by a particular robot device and can determine the total amount of time to relocate the warehouse in this manner. In other instances, the time to perform a particular task by a particular robot may be determined by a high-fidelity simulation of the task in which a simulation is performed to estimate the time to perform the task with the available robots Can be calculated in real time.

At block 310, the method 300 includes determining to relocate items in the warehouse based on the amount of time for relocating the items is less than the threshold amount of time. Thus, in general, if there is an amount of available time for the robot devices to complete the relocation, the WMS will decide to do so. Indeed, relocation can occur overnight, when no human operator is present and the warehouse operation for that day is complete. In some instances, time is the only constraint that is considered when deciding whether to perform an optimization, and is based on the current inventory of the warehouse, future orders, future delivery, number of available robotic devices, current and future battery status of the robotic device , The operation of a robotic device that may collide, etc. may also be considered.

The cost function may associate values with any or all of the parameters considered to generate the cost to relocate the warehouse 100 and if the cost is below a threshold it may be determined that it is advantageous to perform relocation have. The cost function can be maximized or minimized according to parameters or constraints. Depending on the goal to be achieved, an exemplary cost function may include:

F (x) = storage + pallets (A to H) / shipment + open docks

Palettes (A to H) / shipment refers to the requirement to bring these pallets close to the docking station, and open dockyards refer to the requirement to open and make available all dockyards . The values to be associated with these parameters may be based on a 0-100 point system, with zero indicating low priority and 100 indicating mandatory. If the cost function in this exemplary scenario is below a threshold point amount, for example, a relocation may be considered to be recommended, and if relocation can occur at a threshold amount of available time, then the WMS decides to perform relocation. In other examples, the cost function may be set up as a constrained optimization in which an objective function is set with constraints on these variables with respect to some of the variables. The constraint may be a hard constraint that sets the conditions for the variables that are required to be met, or some parameter value that is penalized in the objective function based on the degree to which the conditions on the variables are not met or are not met May be a soft constraint. Here, the cost function can be processed to try to minimize the 95th percentile order fulfillment delay, for example, if all the docks are available. Other goals can also be set.

The value for the cost function may be entered by the user or received by the WMS from the user interface, and a threshold for the cost function may also be set by the user. In additional examples, the input to the cost function can be inferred based on goals that minimize costs or delays or maximize throughput based on predicted and known future incoming and outgoing commodities.

Other exemplary cost functions may also be used and may be used to meet the storage capacity requirements of the warehouse for future dates, as well as future outgoing throughput requirements (e.g., access to items along the drive lane in the warehouse) Storage capacity requirements for dates can also be taken into account for the optimal layout to provide. The throughput throughput of an article also refers to its ability to access the article in a timely manner. For example, if the articles are placed in an area that can not be accessed due to a blocked drive lane, the unloaded items are unpacked and the unloading throughput is delayed.

At block 312, the method 300 includes causing one or more robotic devices to relocate items in the warehouse to an optimal layout. The WMS can send an electronic message (e.g., wirelessly) to each robotic device that notifies a specific job to achieve relocation, and the robotic device can then relocate the items in the warehouse to an optimal layout. The operation may include those described with reference to Figure 1 to move items in the warehouse 100 from one physical location to another physical location or to join the pallets.

In the examples, the robotic device can communicate the progress and completion of the performance of a given task to the WMS. Thus, in response to a message indicating the completion of the performance of a given work step, the WMS may cause at least one of the one or more robot devices to perform another task that is contiguous to the given task.

The method 300 includes more than organizing the items in the warehouse 100 for efficient order fulfillment because the items can be relocated taking into account any number of parameters that weigh the unloading throughput relative to the storage capacity requirement do. The relocation is also performed by an unmanned robot device that operates based on the received command and according to a known time frame for performing the task. Thus, the traditional warehouse environment does not perform large scale relocation because of the inefficiency of large scale relocation or because it is more expensive than the advantages of large scale relocation, but even if small advantages arise, the warehouse 100 is relocated .

The warehouse 100 may be relocated overnight to achieve optimal layout after the day of goods receipt and shipment. The optimal layout can place the warehouse in the optimal configuration for the next business day. In other instances, the warehouse may be relocated during weekly, monthly, seasonally, or any time period during which there is an available amount of time required to perform any desired relocation.

Also, some portions of the warehouse 100 may be relocated while others may remain the same. The WMS is programmable to perform any customized relocation of the warehouse 100.

Figures 4-6 illustrate an exemplary layout of a warehouse. Figure 4 shows an exemplary layout of a warehouse 100 that includes a plurality of article palettes labeled with pallets A-H, and loading docks 110 and 111. In Fig. 4, the pallets A to H are arranged in two rows, and the loading station 111 is blocked.

The optimal layout of the warehouse 100 can be determined so that the loading station 111 is opened and available so that the pallets A to D can be rearranged according to the expected shipment of articles using the loading area 111. [ Figure 5 shows an exemplary relocation of palettes A through H to an optimal layout. For example, the pallets A through D may be relocated to an open row on the other side of the row of pallets E through H. Once the pallets A through D have been relocated, the dockside 111 is now available.

In another example, the optimal layout of the warehouse 100 may be determined such that two loading docks 110 and 111 are open and available. Figure 6 shows an exemplary relocation of the palettes A, E, and F for this layout. For example, each of the pallets A, E, and F may be moved to an adjacent row to provide access to the loading dock 111, while the loading dock 110 may also remain open for use.

Some of these exemplary layouts may also be determined based on availability of the goods close to the loading site and excess inventory of the items may be relocated to storage locations remote from the loading docks 110 and 111. [ As an example, pallets A and F may both contain the same article, so that the excess inventory on pallet F may be located in a storage room facing the rear of the warehouse 100. Or, more simply, the excess inventory on pallet F may be located away from loading docks 110 and 111. In other examples, the layout may be determined by locating the items in the pallet rack (e.g., moving more slowly or placing excess inventory higher in the rack) or by positioning the items in the stacked pallets (e.g., Slower moving or excess inventory may be placed at the bottom of the stack or deeper in the pallet lane).

In yet another example, FIGS. 7-8 illustrate additional layout of the warehouse 100. FIG. FIG. 7 shows an exemplary layout of a warehouse 100 that includes a plurality of article palettes labeled with pallets A-H, and loading docks 110 and 111. New pallets I through K were also delivered and received in the docking station 110. 8 shows an exemplary optimal layout of the warehouse 100 based on the maximum storage capacity placement of the warehouse 100. As shown in FIG. In this example, the pallets are positioned towards the wall of the warehouse, and some pallets such as Palettes C and D, and G and H may be combined. In addition, new pallets I through K of different sizes may also be stacked. This layout shown in FIG. 8 may be for the maximum storage capacity of the warehouse 100, given the size of the pallets in the warehouse 100.

It should be understood that the arrangement described herein is for illustrative purposes only. Thus, it will be appreciated by those of ordinary skill in the art that other arrangements and other elements (e.g., machines, interfaces, operations, sequences, and groupings of operations) It may be omitted altogether. In addition, many of the elements described may be combined in any suitable combination and location, either as individual or distributed components, or as operational entities that may be implemented in conjunction with other components, or as other structural elements described as independent entities .

While various aspects and implementations have been disclosed herein, other aspects and implementations will be apparent to one of ordinary skill in the art. The various aspects and implementations disclosed herein are for the purpose of illustration and are not intended to limit the true scope indicated by the following claims, and the full scope of equivalents to which such claims are entitled. It is also to be understood that the terminology used herein is for the purpose of describing example implementations and is not intended to be limiting.

Claims (20)

As a method,
In a warehouse management system (WMS), receiving real-time inventory of goods in a warehouse and real-time location data of the goods;
Identifying an expected shipment of goods, including new items expected to be received in the warehouse on a future date, and items present in the warehouse marked for delivery on the future date, the identifying step comprising: And based on at least one of a receipt record, an order fulfillment and a shipment record;
Determining an optimal layout of the articles based on the expected shipment of the articles;
Determining an amount of time for the robot device to relocate the articles to the optimal layout based on a time measurement value for the robot device to perform an operation;
Determining to relocate the items of the warehouse based on the amount of time for relocating the items being less than a threshold amount of time; And
Causing the robot device to relocate the articles to the optimal layout
≪ / RTI > 2. The method of claim 1, wherein the items in the warehouse are located on a pallet, and the step of receiving the real-time location data includes receiving information about the contents of each palette as well as positioning the palettes within the warehouse ≪ / RTI > The method of claim 1, further comprising determining an optimal layout of the items based on a business objective including a promotional date for the items. The method of claim 1, further comprising determining an optimal layout of the articles based on a prediction of the quantity of articles to be delivered. The method according to claim 1,
Determining an optimal layout of the articles based on availability of the article proximate the loading site; And
Determining to relocate excess inventory of items to a warehouse remote from the loading dock
≪ / RTI > 2. The method of claim 1, further comprising determining an optimal layout of the items based on a maximum storage capacity arrangement of the warehouse. The method according to claim 1,
At least the following parameters:
The amount of time that inventory is expected to be depleted;
The amount of storage capacity required for incoming goods; And
One or more deadlines for shipment
Further comprising optimizing a layout of the items of the warehouse based on an output of a cost function that takes into account the cost of the warehouse. The method according to claim 1,
Further comprising determining to relocate the items based on the optimal layout to meet outbound throughput of the items and provide storage capacity requirements for the future date. The method according to claim 1,
Further comprising determining to relocate the items of the warehouse based on the storage capacity requirement of the warehouse for the future date. As a system,
A robot device in a warehouse;
A processor; And
A data storage system including instructions executable by the processor to cause the system to perform operations,
The operations comprising:
Receiving real-time inventory of the articles in the warehouse and real-time location data of the articles;
Identifying new shipments expected to arrive at the warehouse at a future date and an expected shipment of goods, including items present in the warehouse marked for delivery on the future date, Based on at least one of order fulfillment records and shipment records;
Determining an optimal layout of the articles based on the shipment estimate;
Determining an amount of time for the robot device to relocate the articles to the optimal layout based on a time measurement value for the robot device to perform an operation;
Determining to relocate the items of the warehouse based on the amount of time for relocating the items being less than a threshold amount of time; And
An operation for causing the robot device to relocate the articles to the optimal layout
. ≪ / RTI > 11. The method of claim 10, wherein the articles in the warehouse are located on pallets, and the act of receiving the real-time location data includes locating the palettes within the warehouse, as well as receiving information about the contents of each palette . ≪ / RTI > 11. The method of claim 10, wherein the operations comprise:
Determining an optimal layout of the articles based on availability of the articles proximate the loading site; And
An operation to decide to relocate an excess inventory of articles to a repository remote from the loading dock
≪ / RTI > 11. The method of claim 10, wherein the operations comprise:
At least the following parameters:
The amount of time that inventory is expected to be depleted;
The amount of storage capacity required for incoming goods; And
One or more deadlines for shipment
Further comprising optimizing a layout of the items of the warehouse based on an output of a cost function that takes into account the cost of the warehouse. 11. The method of claim 10, wherein the operations comprise:
Further comprising determining an optimal layout of the items based on a business objective including a promotional date for the items. 20. A non-transitory computer-readable medium having stored thereon program instructions that, when executed by a computing system comprising at least one processor, cause the computing system to perform operations comprising:
Receiving real-time inventory of goods in the warehouse and real-time location data of the goods;
Identifying new shipments expected to arrive at the warehouse at a future date and an expected shipment of goods, including items present in the warehouse marked for delivery on the future date, Based on one or more of order fulfillment and shipment records;
Determining an optimal layout of the articles based on the shipment estimate;
Determining an amount of time for the robot device to relocate the articles to the optimal layout based on a time measurement value for the robot device to perform an operation;
Determining to relocate the items of the warehouse based on the amount of time for relocating the items being less than a threshold amount of time; And
An operation for causing the robot device to relocate the articles to the optimal layout
Readable medium. ≪ RTI ID = 0.0 > A < / RTI > 16. The method of claim 15, wherein the operations comprise:
Determining an optimal layout of the articles based on availability of the articles proximate the loading site; And
An operation to decide to place an excess inventory of goods in a warehouse remote from the loading dock
≪ / RTI > further comprising a non-transitory computer-readable medium. 16. The method of claim 15, wherein the operations comprise:
At least the following parameters:
The amount of time that inventory is expected to be depleted;
The amount of storage capacity required for incoming goods; And
One or more deadlines for shipment
Further comprising optimizing a layout of the items of the warehouse based on an output of a cost function that takes into account the cost of the warehouse. 16. The method of claim 15, wherein the operations comprise:
Further comprising determining to relocate the articles based on the optimal layout to meet the export throughput of the articles and to provide storage capacity requirements for the future date. 16. The method of claim 15, wherein the operations comprise:
Further comprising determining to relocate the items of the warehouse based on a storage capacity requirement of the warehouse for the future date. 16. The method of claim 15, wherein the operations comprise:
Further comprising determining an optimal layout of the items based on a maximum storage capacity arrangement of the warehouse.

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